Impacts of physical parameterization on prediction of ethane concentrations for oil and gas emissions in WRF-Chem

Abstract

Abstract. Recent increases in natural gas (NG) production through hydraulic fracturing have called the climate benefit of switching from coal-fired to natural gas-fired power plants into question. Higher than expected levels of methane, non-methane hydrocarbons (NMHC), and NOx have been observed in areas close to oil and NG operation facilities. Large uncertainties in the oil and NG operation emission inventories reduce the confidence level in the impact assessment of such activities on regional air quality and climate, as well as in the development of effective mitigation policies. In this work, we used ethane as the indicator of oil and NG emissions and explored the sensitivity of ethane to different physical parameterizations and simulation setups in the Weather Research and Forecasting with Chemistry (WRF-Chem) model using the US EPA National Emission Inventory (NEI-2011). We evaluated the impact of the following configurations and parameterizations on predicted ethane concentrations: planetary boundary layer (PBL) parameterizations, daily re-initialization of meteorological variables, meteorological initial and boundary conditions, and horizontal resolution. We assessed the uncertainties around oil and NG emissions using measurements from the FRAPPÉ and DISCOVER-AQ campaigns over the northern Front Range metropolitan area (NFRMA) in summer 2014. The sensitivity analysis shows up to 57.3 % variability in the normalized mean bias of the near-surface modeled ethane across the simulations, which highlights the important role of model configurations on the model performance and ultimately the assessment of emissions. Comparison between airborne measurements and the sensitivity simulations indicates that the model–measurement bias of ethane ranged from −14.9 to −8.2 ppb (NMB ranged from −80.5 % to −44 %) in regions close to oil and NG activities. Underprediction of ethane concentration in all sensitivity runs suggests an actual underestimation of the oil and NG emissions in the NEI-2011. An increase of oil and NG emissions in the simulations partially improved the model performance in capturing ethane and lumped alkanes (HC3) concentrations but did not impact the model performance in capturing benzene, toluene, and xylene; this is due to very low emission rates of the latter species from the oil and NG sector in NEI-2011.

Chemical Characteristics and Ozone Production in the Northern Colorado Front Range

“…Rather the purpose is to provide a more robust foundation for our conclusions by capturing some of the major underlying model uncertainties. A more detailed discussion on the effects of different model configurations in WRF-Chem simulations for FRAPPÉ is given in Abdi-Oskouei et al (2018). Previous work by Gilliam et al (2015) also provides an in-depth analysis of the impact of uncertainty in meteorology on air quality simulations with WRF-CMAQ over the contiguous United States.…”

Source sector and region contributions to black carbon and PM<sub>2.5</sub> in the Arctic

“…The model used a polar stereographic map projection with 60 km horizontal resolution (249 × 249 grid cells). Regional models such 18128 N. Sobhani et al: Source sector and region contributions to black carbon and PM 2.5 as STEM require initial and boundary conditions from a larger-scale model to achieve reasonable predictions (Abdi-Oskouei et al, 2018;Tang et al, 2007). The STEM model used fixed boundary conditions for these annual simulations.…”

Air Quality in the Northern Colorado Front Range Metro Area: The Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ)

“…. Additional model simulations have also been conducted after the campaign in support of the analysis of observations (e.g.,Abdi-Oskouei et al, 2018;Bahreini et al, 2018;Kaser et al, 2016;Kille et al, 2017;.…”